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Deep Learning: Overview and Trends

Andrew Ng, Associate Professor of Computer Science at Stanford University

Abstract:

Deep learning is the leading approach to many problems in computer vision, speech recognition, NLP, and other areas. In this presentation, I will give a broad overview of deep learning. I will discuss the key reasons for its success, and the important role that scalability plays. I will also describe unsupervised learning approaches to deep learning--such as the "Google cat" result, in which a neural network learned to recognize cats by watching unlabeled YouTube videos--and discuss why this might become increasingly important. Finally, I will discuss recent trends in deep learning, and some possible future applications.

Biography:

Andrew Ng is Chief Scientist of Baidu; Chairman and Co-founder of
Coursera; and an Associate Professor of Computer Science at Stanford
University.
In 2011 he led the development of Stanford University’s main MOOC (Massive
Open Online Courses) platform and also taught an online Machine Learning class
to over 100,000 students, leading to the founding of Coursera. Ng’s goal is
to give everyone access to a great education, for free. Today, Coursera
partners with top universities to offer online courses. With over 9 million
students, it is the world's largest MOOC platform.
Ng also works on machine learning, with an emphasis on deep learning. He had
founded and led the “Google Brain” project, which developed massive-scale deep
learning algorithms. This resulted in the “cat” result, in which a massive
neural network with 1 billion parameters learned from unlabeled YouTube videos
to detect cats. More recently, he is working to build up Baidu Research, which
is developing applications of large scale deep learning to computer vision,
speech, NLP, and other areas.
Recent awards include being named to the Time 100 list of the most influential
people in the world; Fortune 40 under 40; and being named by students as one
of the top 10 professors across Stanford University.